Location: Seattle, WA
Cap-Exempt H-1B Position — No lottery required
Overview: Fred Hutchinson Cancer Center is an independent, nonprofit organization providing adult cancer treatment and groundbreaking research focused on cancer and infectious diseases. Based in Seattle, Fred Hutch is the only National Cancer Institute-designated cancer center in Washington. With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19 vaccines, Fred Hutch has earned a reputation as one of the world’s leading cancer, infectious disease and biomedical research centers. Fred Hutch operates eight clinical care sites that provide medical oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states. Together, our fully integrated research and clinical care teams seek to discover new cures to the world’s deadliest diseases and make life beyond cancer a reality. At Fred Hutch we value collaboration, compassion, determination, excellence, innovation, integrity and respect. Our mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us stronger. We seek employees who bring different and innovative ways of seeing the world and solving problems. The **Data Scientist II** will support clinical and translational data science at the Fred Hutch. The data scientist will use multimodal, real-world healthcare data (electronic health records, registry data, etc.) as well as multimodal data sets generated in clinical and translational labs such as genomics and imaging, to advance our understanding of clinical care and patient outcomes. The data scientist will work on collaborative projects utilizing our OMOP common data model for observational oncology data in combination with diverse multimodal datasets. Projects may include developing predictive clinical models, LLM/AI integrated analyses, statistical model